Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

A Euclidean diffusion model for structure-based drug design.

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

E(2)-Equivariant CNNs Library for Pytorch

A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond

Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/

EquiDock: geometric deep learning for fast rigid 3D protein-protein docking

DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks (ICML 2023)

Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)

[ECCV 2022] Official PyTorch Code of DEVIANT: Depth Equivariant Network for Monocular 3D Object Detection

Implementation of E(n)-Transformer, which incorporates attention mechanisms into Welling's E(n)-Equivariant Graph Neural Network

Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold for protein folding

A library for programmatically generating equivariant layers through constraint solving

Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. This specific repository is geared towards integration with eventual Alphafold2 replication.

A Local Frame-based Atomistic Potential

Multi-domain Distribution Learning for De Novo Drug Design

Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021